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Systematic identification and classification of three-dimensional activity cliffs
Authors:Hu Ye  Furtmann Norbert  Gütschow Michael  Bajorath Jürgen
Institution:Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universit?t, Dahlmannstr. 2, D-53113 Bonn, Germany.
Abstract:Activity cliffs were systematically extracted from public domain X-ray structures of targets for which complexes with multiple ligands were available, following the concept of three-dimensional (3D) cliffs. Binding modes of ligands with well-defined potency measurements were compared in a pairwise manner, and their 3D similarity was calculated using a previously reported property density function-based method taking conformational, positional, and chemical differences into account. Requiring the presence of at least 80% 3D similarity and a potency difference of at least 2 orders of magnitude as cliff criteria, a total of 216 well-defined 3D activity cliffs were detected in the Protein Data Bank (PDB). These 3D-cliffs involved a total of 269 ligands active against 38 different targets belonging to 17 protein families. For 255 of these compounds, binding modes were available at high crystallographic resolution. All 3D-cliffs were analyzed in detail and assigned to different categories on the basis of crystallographic interaction patterns. In many instances, differences in ligand-target interactions suggested plausible causes for origins of 3D-cliffs. In other cases, short-range interactions seen in X-ray structures were insufficient to deduce possible reasons for cliff formation. The 3D-cliffs described herein further advance the rationalization of activity cliffs at the level of ligand-target interactions and should also be useful for other applications such as the calibration of energy functions for structure-based design. The pool of identified activity cliffs is provided to enable subsequent structure-based analyses of cliffs.
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